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dc.contributor.author	FERNANDEZ CERVANTES, VICTOR
dc.contributor.author	GARCIA ROMERO, ARTURO
dc.contributor.author	Ramos Corchado, Marco Antonio
dc.contributor.author	MENDEZ VAZQUEZ, ANDRES
dc.creator	FERNANDEZ CERVANTES, VICTOR; 225750
dc.creator	GARCIA ROMERO, ARTURO; 21359
dc.creator	Ramos Corchado, Marco Antonio; 37345
dc.creator	MENDEZ VAZQUEZ, ANDRES; 95644
dc.date.accessioned	2016-03-16T17:17:56Z
dc.date.available	2016-03-16T17:17:56Z
dc.date.issued	2015
dc.identifier	http://www.redalyc.org/articulo.oa?id=61541546010
dc.identifier.uri	http://hdl.handle.net/20.500.11799/39489
dc.description	Automatic human facial recognition is an important and complicated task; it is necessary to design algorithms capable of recognizing the constant patterns in the face and to use computing resources efficiently. In this paper we present a novel algorithm to recognize the human face in real time; the systems input is the depth and color data from the Microsoft KinectTM device. The algorithm recognizes patterns/shapes on the point cloud topography. The template of the face is based in facial geometry; the forensic theory classifies the human face with respect to constant patterns: cephalometric points, lines, and areas of the face. The topography, relative position, and symmetry are directly related to the craniometric points. The similarity between a point cloud cluster and a pattern description is measured by a fuzzy pattern theory algorithm. The face identification is composed by two phases: the first phase calculates the face pattern hypothesis of the facial points, configures each point shape, the related location in the areas, and lines of the face. Then, in the second phase, the algorithm performs a search on these face point configurations.
dc.format	application/pdf
dc.language.iso	eng	es
dc.publisher	Instituto Politécnico Nacional
dc.relation	http://www.redalyc.org/revista.oa?id=615
dc.rights	Computación y Sistemas
dc.rights	openAccess	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0
dc.source	Computación y Sistemas (México) Num.3 Vol.19
dc.subject	Computación	es
dc.subject	Kinect	es
dc.subject	RGBD	es
dc.subject	fuzzy logic	es
dc.subject	face detection	es
dc.subject	face segmentation	es
dc.subject.classification	INGENIERÍA Y TECNOLOGÍA
dc.title	Facial Geometry Identification through Fuzzy Patterns with RGBD Sensor	es
dc.type	Artículo	es
dc.provenance	Científica	es
dc.road	Dorada	es
dc.ambito	Internacional	es
dc.audience	students	es
dc.audience	researchers	es
dc.type.conacyt	article
dc.identificator	7

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